From the 1 of 12 linked papers with an AI index.
12 papers
Complementary Matrix-Gated QKAN Fast-Weight Programmers for Quantum Dynamics Forecasting
Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +14
The paper proposes Complementary Matrix Gating, a coordinate‑wise gating scheme for fast‑weight programmers built on quantum‑inspired Kolmogorov‑Arnold networks, and shows it impro…
Stable Self-Modulating Quantum Fast-Weight Programmers with Bounded Memory Gates
Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +8
Quantum Fast-Weight Programmers (QFWPs) store temporal information in dynamically programmed variational-circuit parameters rather than in nonlinear recurrent hidden states, offeri…
Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting
Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +3
Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting remains challenging when predict…
Self-Modulating Quantum Fast-Weight Programmers for Efficient Adaptive Sequential Learning
Samuel Yen-Chi Chen, Yifeng Peng, Kuo-Chung Peng +8
Recent advances in quantum machine learning have motivated efficient models for sequential data processing. In this paper, we propose Self-Modulating Quantum Fast Weight Programmer…
Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation
Samuel Yen-Chi Chen, Yifeng Peng, Jiun-Cheng Jiang +8
Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this paper, we propose a Recursive Qua…
Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning
Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +16
Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (QFWPs) extend this idea with v…